Tomasz P. Zielinski

DFT-based Estimation of Damped Oscillation Parameters in Low-Frequency Mechanical Spectroscopy

In this paper, we analyze and compare the properties of different well-known and also new nonparametric discrete Fourier transform (DFT)-based methods for resonant frequency and logarithmic decrement estimation in application to mechanical spectroscopy. We derive a new DFT interpolation algorithm for a signal analyzed with Rife-Vincent class-I windows and also propose new formulas that extend Bertocco and Yoshida methods. We study errors of the resonant frequency and logarithmic decrement estimation in realistic conditions that include measurement noise and a zero-point drift. We also investigate the systematic errors of the estimation methods of interest. A nonlinear least squares time-domain parametric signal fitting is used to determine the boundaries of statistical efficiency in all tests.

Data Processing Tasks in Wireless GI Endoscopy: Image-Based Capsule Localization & Navigation and Video Compression

The paper addresses data processing support that is required in capsule gastrointestinal endoscopy. First, capsule position estimation method using standard MPEG-7 image features (descriptors) is discussed. The proposed approach makes use of vector quantization, principal component analysis and neural networks. Next, new algorithms dedicated for virtual colonoscopy (VC) human body inspection are described. The VC images can be registered with endoscopic ones and help in capsule localization and navigation. Finally, an original, low- complexity, efficient image compression method, based on integer-to-integer 4x4 DCT transform, is presented and experimentally verified.

Joint time-frequency resolution of signal analysis using Gabor transform

A joint time-frequency (TF) resolution of the Gabor transform-based signal analysis is investigated. First, different window functions used in the Gabor transform are compared with regard to their time duration and frequency bandwidth. Next, optimal windows with small TF support are found. Finally, a practical choice of windows maximizing signal energy concentration in the TF domain is examined. In this case, the error of signal reconstruction from the Gabor coefficients and the mean square width of the short-time signal spectrum are computed for different time-varying test signals and minimized in the optimization process. An appropriate adaptation of the window length according to the rate of frequency modulation is discussed.

Hardware Implementation Aspects of New Low Complexity Image Coding Algorithm for Wireless Capsule Endoscopy

The paper presents hardware implementation aspects of new efficient image compression algorithm designed for wireless capsule endoscopy with Bayer color filter array (CFA). Since power limitation, small size conditions and specific image data format (CFA) exclude application of traditional image compression techniques dedicated ones are necessary. Discussed algorithm is based on integer version of discrete cosine transform (DCT). Therefore it has low complexity and power consumption. It is demonstrated that the perfor-mance of proposed algorithm is comparable to the performance of JPEG2000 --- very complex, sophisticated wavelet based coder. In the paper a VLSI coder architecture is proposed and power requirements are discussed.

Image denoising using scale-adaptive lifting schemes

The paper addresses the problem of image denoising using adaptive wavelet transforms. Two scale-adaptive versions of the wavelet transform are implemented and experimentally tested: the classical and the lifting one. In both of them exemplary test images are contaminated with noise, decomposed into several multiresolution levels, modified via soft thresholding (only detail subimages) and inversely synthesized. On each level the LL image from the previous stage is decomposed into LL, LH, HL and HIT subimages using different wavelet or predict/update lifting filters (L-lowpass, H-highpass). At each level as the best filters are chosen such ones, for which the normalized energy of the detail HH subimage is the lowest. Image denoising is realized by soft thresholding of all detail HH subimages only. Several test images are processed in the paper. Explicit equations for the design of lifting filters are presented.

Lossless ECG compression with lifting wavelet transform

The paper presents a new algorithm for lossless ECG compression using lifting wavelet transform. The transform is implemented in its integers to integers version, and thus quantization of wavelet coefficients and rounding of errors are avoided. A new adaptation method for the wavelet lifting transform is presented. The efficiency of adaptive lifting transform is compared with DPCM coding and S+P transform.

Joint Application of Audio Spectral Envelope and Tonality Index in an E-Asthma Monitoring System

This paper presents in detail a recently introduced highly efficient method for automatic detection of asthmatic wheezing in breathing sounds. The fluctuation in the audio spectral envelope (ASE) from the MPEG-7 standard and the value of the tonality index (TI) from the MPEG-2 Audio specification are jointly used as discriminative features for wheezy sounds, while the support vector machine (SVM) with a polynomial kernel serves as a classifier. The advantages of the proposed approach are described in the paper (e.g., detecting weak wheezes, very good ROC characteristics, independence from noise color). Since the method is not computationally complex, it is suitable for remote asthma monitoring using mobile devices (personal medical assistants). The main contribution of this paper consists of presenting all the implementation details concerning the proposed approach for the first time, i.e., the pseudocode of the method and adjusting the values of the ASE and TI parameters after which only one (not two) FFT is required for analysis of a next overlapping signal fragment. The efficiency of the method has also been additionally confirmed by the AdaBoost classifier with a built-in mechanism to feature ranking, as well as a previously performed minimal-redundancy-maximal-relevance test.

Computed tomography-based radiotherapy planning on the example of prostate cancer: application of level-set segmentation method guided by atlas-type knowledge

In this invited paper an overview of the Computed Tomography-based cancer radiotherapy planning is given. All planning steps are described with details, i.e. its goals, existing solutions and typical realizations. On this background, as an example, a complete procedure of prostate cancer radiotherapy planning is presented in which application of Level-Set segmentation method guided by a priori atlas-type knowledge is proposed. Developed procedure was verified on data base consisting of 266 CT slices of 4 patients.

Localization of Endoscopic Capsule in the GI Tract Based on MPEG-7 Visual Descriptors

The paper addresses the problem of localization of video endoscopic capsule in the gastrointestinal (GI) tract on the base of appropriate classification of images received from it. In this context usefulness of MPEG-7 image descriptors as classification features has been verified. For classification purpose various state of the art tools were used including Neural Networks and Vector Quantization. The dimension of the problem was also reduced by the Principal Component Analysis. Novelty of the presented approach consists in joint application of mentioned above techniques for recognition of the GI region inspected by the capsule by means of classification of MPEG-7 features to different parts of GI tract. In this research recognition of the upper part organs of the GI tract has been performed.

Efficacy of the frequency and damping estimation of a real-value sinusoid Part 44 in a series of tutorials on instrumentation and measurement

Sinusoidal and damped sinusoidal signals are common in different branches of engineering. Estimation of frequency and damping is very important in many fields [1]–[15], e.g., linear system identification, speech processing, image processing, transient analysis, electric power system analysis, radar and sonar systems, communication, nuclear magnetic resonance spectroscopy (NMRS), mechanical spectroscopy, economics, seismology, and others. The literature on the subject is very rich. Recently an interesting introduction to frequency and damping estimation methods was published in the IEEE Instrumentation & Measurement Magazine [15]. In this paper, we focus on the methods with the best performance for a single component, damped, real-valued sinusoidal signal disturbed by additive white Gaussian noise. In our previous works [14] and [16]–[18], we investigated these estimation methods, two-point and three-point interpolated Discrete Fourier Transform (IpDFT) for an undamped sinusoidal signal analyzed with Rife-Vincent class I, Kaiser-Bessel and Dolph-Chebyshev windows, methods of Bertocco, Yoshida and Bertocco-Yoshida family for orders 0-3, the Agrez algorithm, IpDFT for damped sinusoidal signal analyzed with Rife-Vincent class I windows, time domain and frequency domain Least Squares (LS) optimization, Hilbert transform, covariance, Prony, iterative Steiglitz-McBride (STMB), Kumaresan-Tufts, total least squares, Matrix Pencil (MatPen), and Pisarenko. For this presentation, we choose only the best methods from the above set, i.e. the Bertocco-Yoshida order 1 (BY1) STMB and MatPen. We also describe the iterative leakage correction algorithm [19] with application to BY1, and compare all results with the well-known Aboutanios and Mulgrew algorithm (AbM) [13]. Our intention is to describe and compare the best existing algorithms. We consider a real-valued signal because it is a typical measurement case. The DFT spectrum of this signal is disturbed by a spectral leakage [5].